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Grouping based radio frequency identification anti-collision protocols for dense internet of things application

Radio frequency identification (RFID) is an important internet of things (IoT) enabling technology. In RFIDs collision occur among tags because tags share communication channel. This is called tag collision problem. The problem becomes catastrophic when dense population of tags are deployed like in...

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Main Authors: Umelo, Nnamdi H., Noordin, Nor K., A. Rasid, Mohd Fadlee, Geok, Tan K., Hashim, Fazirulhisyam
Format: Article
Published: Institute of Advanced Engineering and Science IAES 2022
Online Access:http://psasir.upm.edu.my/id/eprint/101660/
https://ijece.iaescore.com/index.php/IJECE/article/view/28446
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spelling my.upm.eprints.1016602023-09-21T03:51:23Z http://psasir.upm.edu.my/id/eprint/101660/ Grouping based radio frequency identification anti-collision protocols for dense internet of things application Umelo, Nnamdi H. Noordin, Nor K. A. Rasid, Mohd Fadlee Geok, Tan K. Hashim, Fazirulhisyam Radio frequency identification (RFID) is an important internet of things (IoT) enabling technology. In RFIDs collision occur among tags because tags share communication channel. This is called tag collision problem. The problem becomes catastrophic when dense population of tags are deployed like in IoT. Hence, the need to enhance existing dynamic frame slotted ALOHA (DFSA) based electronic product code (EPC) C1G2 media access control (MAC) protocol. Firstly, this paper validates through simulation the DFSA theory that efficiency of the RFID system is maximum when the number tags is approximately equal to the frame size. Furthermore, literature review shows tag grouping is becoming popular to improving the efficiency of the RFID system. This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. The algorithms were implemented in MATLAB while extensive Monte Carlo simulation was performed to evaluate their strengths and weaknesses. Results show that with higher tag density, fuzzy C-means based algorithm (FCMBG) outperformed traditional DFSA by over 40% in terms of throughput rate. The results also demonstrate FCMBG bettered other grouping-based algorithms (GB-DFSA and GBSA) whose tag estimation method are based on collision slots in terms slot efficiency by over 10% and also in terms of identification time. Institute of Advanced Engineering and Science IAES 2022 Article PeerReviewed Umelo, Nnamdi H. and Noordin, Nor K. and A. Rasid, Mohd Fadlee and Geok, Tan K. and Hashim, Fazirulhisyam (2022) Grouping based radio frequency identification anti-collision protocols for dense internet of things application. International Journal of Electrical and Computer Engineering, 12 (6). 5848 - 5860. ISSN 2088-8708; ESSN: 2722-2578 https://ijece.iaescore.com/index.php/IJECE/article/view/28446 10.11591/ijece.v12i6.pp5848-5860
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
description Radio frequency identification (RFID) is an important internet of things (IoT) enabling technology. In RFIDs collision occur among tags because tags share communication channel. This is called tag collision problem. The problem becomes catastrophic when dense population of tags are deployed like in IoT. Hence, the need to enhance existing dynamic frame slotted ALOHA (DFSA) based electronic product code (EPC) C1G2 media access control (MAC) protocol. Firstly, this paper validates through simulation the DFSA theory that efficiency of the RFID system is maximum when the number tags is approximately equal to the frame size. Furthermore, literature review shows tag grouping is becoming popular to improving the efficiency of the RFID system. This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. The algorithms were implemented in MATLAB while extensive Monte Carlo simulation was performed to evaluate their strengths and weaknesses. Results show that with higher tag density, fuzzy C-means based algorithm (FCMBG) outperformed traditional DFSA by over 40% in terms of throughput rate. The results also demonstrate FCMBG bettered other grouping-based algorithms (GB-DFSA and GBSA) whose tag estimation method are based on collision slots in terms slot efficiency by over 10% and also in terms of identification time.
format Article
author Umelo, Nnamdi H.
Noordin, Nor K.
A. Rasid, Mohd Fadlee
Geok, Tan K.
Hashim, Fazirulhisyam
spellingShingle Umelo, Nnamdi H.
Noordin, Nor K.
A. Rasid, Mohd Fadlee
Geok, Tan K.
Hashim, Fazirulhisyam
Grouping based radio frequency identification anti-collision protocols for dense internet of things application
author_facet Umelo, Nnamdi H.
Noordin, Nor K.
A. Rasid, Mohd Fadlee
Geok, Tan K.
Hashim, Fazirulhisyam
author_sort Umelo, Nnamdi H.
title Grouping based radio frequency identification anti-collision protocols for dense internet of things application
title_short Grouping based radio frequency identification anti-collision protocols for dense internet of things application
title_full Grouping based radio frequency identification anti-collision protocols for dense internet of things application
title_fullStr Grouping based radio frequency identification anti-collision protocols for dense internet of things application
title_full_unstemmed Grouping based radio frequency identification anti-collision protocols for dense internet of things application
title_sort grouping based radio frequency identification anti-collision protocols for dense internet of things application
publisher Institute of Advanced Engineering and Science IAES
publishDate 2022
url http://psasir.upm.edu.my/id/eprint/101660/
https://ijece.iaescore.com/index.php/IJECE/article/view/28446
_version_ 1781706702222000128
score 13.211869

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